R-Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

R

r - Variable in class burlap.behavior.singleagent.learning.lspi.SARSData.SARS: The resulting reward received
r - Variable in class burlap.mdp.singleagent.environment.EnvironmentOutcome: The reward received
rand - Variable in class burlap.behavior.functionapproximation.sparse.tilecoding.TileCodingFeatures: A random object for jittering the tile alignments.
rand - Variable in class burlap.behavior.policy.EpsilonGreedy
rand - Variable in class burlap.behavior.policy.GreedyQPolicy
rand - Variable in class burlap.behavior.policy.RandomPolicy: The random factory used to randomly select actions.
rand - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL: A random object used for initializing each cluster's RF parameters randomly.
rand - Variable in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS: A random object for random walks
rand - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
rand - Variable in class burlap.behavior.stochasticgames.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingSGAgent: Random generator for selecting actions according to the solved solution
rand - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.policies.EGreedyJointPolicy: A random object used for sampling
rand - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.policies.EGreedyMaxWellfare: A random object used for sampling
rand - Variable in class burlap.datastructures.BoltzmannDistribution: The random object to use for sampling.
rand - Variable in class burlap.datastructures.StochasticTree: A random object used for sampling.
rand - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphActionType: Random object for sampling the stochastic graph transitions
rand - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphStateModel
rand - Variable in class burlap.domain.singleagent.gridworld.GridWorldDomain.GridWorldModel
RandomFactory - Class in burlap.debugtools: Random factory that allows you to logically group various random generators.
RandomFactory() - Constructor for class burlap.debugtools.RandomFactory: Initializes the map structures
randomizeParameters(DifferentiableRF) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL: Randomizes the parameters for a given DifferentiableRF.
randomizeParameters(double[]) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL: Randomizes parameters in the given vector between -1 and 1.
RandomPolicy - Class in burlap.behavior.policy: A uniform random policy for single agent domains.
RandomPolicy(SADomain) - Constructor for class burlap.behavior.policy.RandomPolicy: Initializes by copying all the primitive actions references defined for the domain into an internal action list for this policy.
RandomPolicy(List<ActionType>) - Constructor for class burlap.behavior.policy.RandomPolicy: Initializes by copying all the actions references defined in the provided list into an internal action list for this policy.
RandomSGAgent - Class in burlap.behavior.stochasticgames.agents: Stochastic games agent that chooses actions uniformly randomly.
RandomSGAgent() - Constructor for class burlap.behavior.stochasticgames.agents.RandomSGAgent
randomSideStateGenerator() - Static method in class burlap.domain.singleagent.pomdp.tiger.TigerDomain: Returns a StateGenerator that 50% of the time generates an hidden tiger state with the tiger on the left side, and 50% time on the right.
randomSideStateGenerator(double) - Static method in class burlap.domain.singleagent.pomdp.tiger.TigerDomain: Returns a StateGenerator that some of the of the time generates an hidden tiger state with the tiger on the left side, and others on the right.
RandomStartStateGenerator - Class in burlap.mdp.auxiliary.common: This class will return a random state from a set of states that are reachable from a source seed state.
RandomStartStateGenerator(SADomain, State) - Constructor for class burlap.mdp.auxiliary.common.RandomStartStateGenerator: Will discover the reachable states from which to randomly select.
RandomStartStateGenerator(SADomain, State, HashableStateFactory) - Constructor for class burlap.mdp.auxiliary.common.RandomStartStateGenerator: Will discover reachable states from which to randomly select.
RBF - Class in burlap.behavior.functionapproximation.dense.rbf: A class for defining radial basis functions for states represented with a double array.
RBF(double[], DistanceMetric) - Constructor for class burlap.behavior.functionapproximation.dense.rbf.RBF: Initializes.
RBFFeatures - Class in burlap.behavior.functionapproximation.dense.rbf: A feature database of RBF units that can be used for linear value function approximation.
RBFFeatures(DenseStateFeatures, boolean) - Constructor for class burlap.behavior.functionapproximation.dense.rbf.RBFFeatures: Initializes with an empty list of RBF units.
rbfs - Variable in class burlap.behavior.functionapproximation.dense.rbf.RBFFeatures: The list of RBF units in this database
read(String) - Static method in class burlap.behavior.singleagent.Episode: Reads an episode that was written to a file and turns into an EpisodeAnalysis object.
read(String) - Static method in class burlap.behavior.stochasticgames.GameEpisode: Reads a game that was written to a file and turns into a GameEpisode object.
read() - Method in class burlap.shell.visual.TextAreaStreams.TextIn
readEpisodes(String) - Static method in class burlap.behavior.singleagent.Episode: Takes a path to a directory containing .episode files and reads them all into a List of Episode objects.
recCommand - Variable in class burlap.shell.command.env.EpisodeRecordingCommands
receiveInput(String) - Method in class burlap.shell.visual.TextAreaStreams: Adds data to the InputStream
recomputeReachableStates() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableVI: Calling this method will force the valueFunction to recompute the reachable states when the DifferentiableVI.planFromState(State) method is called next.
recomputeReachableStates() - Method in class burlap.behavior.singleagent.planning.stochastic.policyiteration.PolicyIteration: Calling this method will force the valueFunction to recompute the reachable states when the PolicyIteration.planFromState(State) method is called next.
recomputeReachableStates() - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.ValueIteration: Calling this method will force the valueFunction to recompute the reachable states when the ValueIteration.planFromState(State) method is called next.
RecordCommand() - Constructor for class burlap.shell.command.env.EpisodeRecordingCommands.RecordCommand
recordedLast - Variable in class burlap.shell.command.env.EpisodeRecordingCommands
recording - Variable in class burlap.shell.command.env.EpisodeRecordingCommands
referencesSuccessor(UCTStateNode) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTActionNode: Returns whether this action node has a observed a given successor state node in the past
ReflectiveHashableStateFactory - Class in burlap.statehashing: A HashableState factory to use when the source State objects by default implement the HashableState interface.
ReflectiveHashableStateFactory() - Constructor for class burlap.statehashing.ReflectiveHashableStateFactory
refreshPriority(T) - Method in class burlap.datastructures.HashIndexedHeap: Calling this method indicates that the priority of the object passed to the method has been modified and that this heap needs to reorder its elements as a result
regCommand - Variable in class burlap.shell.command.world.ManualAgentsCommands
RegisterAgentCommand() - Constructor for class burlap.shell.command.world.ManualAgentsCommands.RegisterAgentCommand
remove(int) - Method in class burlap.behavior.singleagent.learning.lspi.SARSData: Removes the SARSData.SARS tuple at the ith index
remove(T) - Method in class burlap.datastructures.StochasticTree: Removes the given element from the tree.
removeAction(String) - Method in class burlap.behavior.policy.RandomPolicy: Removes an action from consideration.
removeAlias(String) - Method in class burlap.shell.BurlapShell
removeAttributeMasks(Object...) - Method in class burlap.statehashing.masked.MaskedConfig: Removes variable masks.
removeAttributeMasks(Object...) - Method in class burlap.statehashing.masked.MaskedHashableStateFactory: Removes variable masks.
removeCommand(String) - Method in class burlap.shell.BurlapShell
removeEdge(int, int, int) - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Removes a given edge from the transition dynamics.
removeHelper(StochasticTree<T>.STNode) - Method in class burlap.datastructures.StochasticTree: A recursive method for removing a node
removeObject(String) - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeState
removeObject(String) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldState
removeObject(String) - Method in class burlap.domain.singleagent.frostbite.state.FrostbiteState
removeObject(String) - Method in class burlap.domain.singleagent.gridworld.state.GridWorldState
removeObject(String) - Method in class burlap.domain.singleagent.lunarlander.state.LLState
removeObject(String) - Method in class burlap.mdp.core.oo.state.generic.GenericOOState
removeObject(String) - Method in interface burlap.mdp.core.oo.state.MutableOOState: Removes the object instance with the name oname from this state.
removeObjectClassMasks(String...) - Method in class burlap.statehashing.masked.MaskedConfig: Removes masks for OO-MDP object classes
removeObjectClassMasks(String...) - Method in class burlap.statehashing.masked.MaskedHashableStateFactory: Removes masks for OO-MDP object classes
removeObservers(EnvironmentObserver...) - Method in class burlap.mdp.singleagent.environment.extensions.EnvironmentServer: Removes one or more EnvironmentObservers from this server.
removeObservers(EnvironmentObserver...) - Method in interface burlap.mdp.singleagent.environment.extensions.EnvironmentServerInterface: Removes one or more EnvironmentObservers from this server.
removeObservers(EnvironmentObserver...) - Method in class burlap.mdp.singleagent.environment.SimulatedEnvironment
removeRenderLayer(int) - Method in class burlap.visualizer.MultiLayerRenderer: Removes the render layer at teh specified position.
RemoveStateObjectCommand - Class in burlap.shell.command.env: A ShellCommand for removing an OO-MDP object from the current Environment State.
RemoveStateObjectCommand() - Constructor for class burlap.shell.command.env.RemoveStateObjectCommand
RemoveStateObjectSGCommand - Class in burlap.shell.command.world: A ShellCommand for removing an OO-MDP object from the current World State.
RemoveStateObjectSGCommand() - Constructor for class burlap.shell.command.world.RemoveStateObjectSGCommand
removeTerminals(int...) - Method in class burlap.domain.singleagent.graphdefined.GraphTF: Removes nodes as being marked as terminal states
removeWorldObserver(WorldObserver) - Method in class burlap.mdp.stochasticgames.world.World: Removes the specified world observer from this world
removeZeroRows(double[][]) - Static method in class burlap.behavior.stochasticgames.solvers.CorrelatedEquilibriumSolver: Takes an input 2D double matrix and returns a new matrix will all the all zero rows removed.
renameObject(String, String) - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeState
renameObject(String, String) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldState
renameObject(String, String) - Method in class burlap.domain.singleagent.frostbite.state.FrostbiteState
renameObject(String, String) - Method in class burlap.domain.singleagent.gridworld.state.GridWorldState
renameObject(String, String) - Method in class burlap.domain.singleagent.lunarlander.state.LLState
renameObject(String, String) - Method in class burlap.mdp.core.oo.state.generic.GenericOOState
renameObject(String, String) - Method in interface burlap.mdp.core.oo.state.MutableOOState: Renames the identifier for object instance o in this state to newName.
renameObjects(GridWorldState) - Method in class burlap.testing.TestHashing
render(Graphics2D, float, float) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.PolicyRenderLayer
render(Graphics2D, float, float) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionRenderLayer
render(Graphics2D, float, float) - Method in interface burlap.visualizer.RenderLayer
render(Graphics2D, float, float) - Method in class burlap.visualizer.StateActionRenderLayer
render(Graphics2D, float, float) - Method in class burlap.visualizer.StateRenderLayer
renderAction - Variable in class burlap.visualizer.StateActionRenderLayer: The current Action to render
RenderLayer - Interface in burlap.visualizer: A RenderLayer is a 2 dimensional layer that paints to a provided 2D graphics context.
renderLayers - Variable in class burlap.visualizer.MultiLayerRenderer: The layers that will be rendered in order from index 0 to n
renderState - Variable in class burlap.visualizer.StateActionRenderLayer: The current State to render
renderStateAction(Graphics2D, State, Action, float, float) - Method in class burlap.visualizer.StateActionRenderLayer: Method to be implemented by subclasses that will render the input state-action to the given graphics context.
renderStyle - Variable in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.PolicyGlyphPainter2D: The render style to use
renderValueString - Variable in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.StateValuePainter2D: Whether the numeric string for the value of the state should be rendered in its cell or not.
repaintOnActionInitiation - Variable in class burlap.mdp.singleagent.common.VisualActionObserver: If true, then a a state-action pair is rendered on calls to VisualActionObserver.observeEnvironmentActionInitiation(State, Action) so long as the input Visualizer has a set StateActionRenderLayer.
repaintStateOnEnvironmentInteraction - Variable in class burlap.mdp.singleagent.common.VisualActionObserver: If true (which is default), then the post-state in an VisualActionObserver.observeEnvironmentInteraction(burlap.mdp.singleagent.environment.EnvironmentOutcome) is rendered.
replayGame(GameEpisode) - Method in class burlap.mdp.stochasticgames.common.VisualWorldObserver: Causes the visualizer to be replayed for the given GameEpisode object.
request - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.MLIRL: The MLRIL request defining the IRL problem.
request - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL: The source problem request defining the problem to be solved.
requireMarkov - Variable in class burlap.behavior.singleagent.options.model.BFSMarkovOptionModel
rerunVI() - Method in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelLearningPlanner: Reruns VI on the new updated model.
rescale(double, double) - Method in interface burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.ColorBlend: Tells this object the minimum value and the maximum value it can receive.
rescale(double, double) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.LandmarkColorBlendInterpolation
rescale(double, double) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.StateValuePainter2D
rescale(double, double) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.StateValuePainter: Used to tell this painter that it should render state values so that the minimum possible value is lowerValue and the maximum is upperValue.
rescaleRect(float, float, float, float, float) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.PolicyGlyphPainter2D: Takes in a rectangle specification and scales it equally along each direction by a scale factor.
reserved - Variable in class burlap.shell.BurlapShell
resetAvgs() - Method in class burlap.debugtools.MyTimer: Resets to zero the average and total time recorded over all start-stop calls.
resetData() - Method in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor
resetData() - Method in class burlap.behavior.singleagent.learning.actorcritic.Actor: Used to reset any data that was created/modified during learning so that learning can be begin anew.
resetData() - Method in interface burlap.behavior.singleagent.learning.actorcritic.Critic: Used to reset any data that was created/modified during learning so that learning can be begin anew.
resetData() - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
resetData() - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda
resetDecay() - Method in class burlap.behavior.functionapproximation.dense.fourier.FourierBasisLearningRateWrapper
resetDecay() - Method in class burlap.behavior.learningrate.ConstantLR
resetDecay() - Method in class burlap.behavior.learningrate.ExponentialDecayLR
resetDecay() - Method in interface burlap.behavior.learningrate.LearningRate: Causes any learnign rate decay to reset to where it started.
resetDecay() - Method in class burlap.behavior.learningrate.SoftTimeInverseDecayLR
ResetEnvCommand - Class in burlap.shell.command.env: A ShellCommand for resetting the Environment.
ResetEnvCommand() - Constructor for class burlap.shell.command.env.ResetEnvCommand
resetEnvironment() - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent
resetEnvironment() - Method in class burlap.behavior.stochasticgames.agents.interfacing.singleagent.LearningAgentToSGAgentInterface
resetEnvironment() - Method in interface burlap.mdp.singleagent.environment.Environment: Resets this environment to some initial state, if the functionality exists.
resetEnvironment() - Method in class burlap.mdp.singleagent.environment.extensions.EnvironmentServer
resetEnvironment() - Method in class burlap.mdp.singleagent.environment.SimulatedEnvironment
resetEnvironment() - Method in class burlap.mdp.singleagent.pomdp.SimulatedPOEnvironment
resetMatchSelections() - Method in class burlap.mdp.stochasticgames.tournament.common.AllPairWiseSameTypeMS
resetMatchSelections() - Method in interface burlap.mdp.stochasticgames.tournament.MatchSelector: Resets the match selections and causes the MatchSelector.getNextMatch() method to start from the beginning of matches
resetModel() - Method in interface burlap.behavior.singleagent.learning.modellearning.LearnedModel: Resets the model data so that learning can begin anew.
resetModel() - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
resetModel() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.RMaxModel
resetParameters() - Method in class burlap.behavior.functionapproximation.dense.DenseLinearVFA
resetParameters() - Method in class burlap.behavior.functionapproximation.dense.DenseStateActionLinearVFA
resetParameters() - Method in interface burlap.behavior.functionapproximation.ParametricFunction: Resets the parameters of this function to default values.
resetParameters() - Method in class burlap.behavior.functionapproximation.sparse.LinearVFA
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateActionDifferentiableRF
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateDifferentiableRF
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearStateDiffVF
resetParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.VanillaDiffVinit
resetSolver() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableDP
resetSolver() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling
resetSolver() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableVI
resetSolver() - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic
resetSolver() - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
resetSolver() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
resetSolver() - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
resetSolver() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax
resetSolver() - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
resetSolver() - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
resetSolver() - Method in class burlap.behavior.singleagent.MDPSolver
resetSolver() - Method in interface burlap.behavior.singleagent.MDPSolverInterface: This method resets all solver results so that a solver can be restarted fresh as if had never solved the MDP.
resetSolver() - Method in class burlap.behavior.singleagent.planning.deterministic.DeterministicPlanner
resetSolver() - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
resetSolver() - Method in class burlap.behavior.singleagent.planning.stochastic.DynamicProgramming
resetSolver() - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
resetSolver() - Method in class burlap.behavior.singleagent.planning.stochastic.policyiteration.PolicyIteration
resetSolver() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling
resetSolver() - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.ValueIteration
resetSolver() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI
resetSolver() - Method in class burlap.behavior.singleagent.pomdp.qmdp.QMDP
resetSolver() - Method in class burlap.behavior.singleagent.pomdp.wrappedmdpalgs.BeliefSparseSampling
resetTournamentReward() - Method in class burlap.mdp.stochasticgames.tournament.Tournament: Reset the cumulative reward received by each agent in this tournament.
resolveCollisions(List<GridGameStandardMechanics.Location2>, List<GridGameStandardMechanics.Location2>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Resolves collisions that occur when two or more agents try to enter the same cell, in which case only one agent will make it into the position and the rest will stay in place
resolveCommand(String) - Method in class burlap.shell.BurlapShell
resolvePositionSwaps(List<GridGameStandardMechanics.Location2>, List<GridGameStandardMechanics.Location2>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Returns the position of each agent after accounting for collisions that are a result of agents trying to move into each others previous locations.
responseFor(double[]) - Method in class burlap.behavior.functionapproximation.dense.rbf.functions.GaussianRBF
responseFor(double[]) - Method in class burlap.behavior.functionapproximation.dense.rbf.RBF: Returns the RBF response from its center state to the query input state.
returnCode - Variable in class burlap.shell.ShellObserver.ShellCommandEvent: The return code of the command.
reverseEnumerate - Variable in class burlap.behavior.singleagent.auxiliary.StateEnumerator: The reverse enumeration id to state map
reward(int) - Method in class burlap.behavior.singleagent.Episode: Returns the reward received at timestep t.
reward(State, Action, State) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateActionDifferentiableRF
reward(State, Action, State) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateDifferentiableRF
reward(State, Action, State) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
reward(State, Action, State) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
reward(State, Action, State) - Method in class burlap.behavior.singleagent.shaping.ShapedRewardFunction
reward(State, Action, State) - Method in class burlap.domain.singleagent.cartpole.CartPoleDomain.CartPoleRewardFunction
reward(State, Action, State) - Method in class burlap.domain.singleagent.cartpole.InvertedPendulum.InvertedPendulumRewardFunction
reward(State, Action, State) - Method in class burlap.domain.singleagent.frostbite.FrostbiteRF
reward(State, Action, State) - Method in class burlap.domain.singleagent.graphdefined.GraphRF
reward(int, int, int) - Method in class burlap.domain.singleagent.graphdefined.GraphRF: Returns the reward for taking action a in state node s and transition to state node sprime.
reward(State, Action, State) - Method in class burlap.domain.singleagent.gridworld.GridWorldRewardFunction
reward(State, Action, State) - Method in class burlap.domain.singleagent.lunarlander.LunarLanderRF
reward(State, JointAction, State) - Method in class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction
reward(State, JointAction, State) - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.SingleStageNormalFormJointRewardFunction
reward(State, Action, State) - Method in class burlap.mdp.singleagent.common.GoalBasedRF
reward(State, Action, State) - Method in class burlap.mdp.singleagent.common.NullRewardFunction
reward(State, Action, State) - Method in class burlap.mdp.singleagent.common.SingleGoalPFRF
reward(State, Action, State) - Method in class burlap.mdp.singleagent.common.UniformCostRF
reward(State, Action, State) - Method in interface burlap.mdp.singleagent.model.RewardFunction: Returns the reward received when action a is executed in state s and the agent transitions to state sprime.
reward(State, JointAction, State) - Method in class burlap.mdp.stochasticgames.common.NullJointRewardFunction
reward(State, JointAction, State) - Method in interface burlap.mdp.stochasticgames.model.JointRewardFunction: Returns the reward received by each agent specified in the joint action.
RewardCommand - Class in burlap.shell.command.env: A ShellCommand for checking the last reward received from the Environment.
RewardCommand() - Constructor for class burlap.shell.command.env.RewardCommand
rewardFunction - Variable in class burlap.behavior.singleagent.learnfromdemo.CustomRewardModel
rewardFunction() - Method in class burlap.mdp.singleagent.model.FactoredModel
RewardFunction - Interface in burlap.mdp.singleagent.model: Defines the reward function for a task.
rewardFunction() - Method in interface burlap.mdp.singleagent.model.TaskFactoredModel: Returns the RewardFunction this model uses to compute rewards
rewardMatrix - Variable in class burlap.domain.singleagent.gridworld.GridWorldRewardFunction
rewardRange - Variable in class burlap.domain.singleagent.rlglue.RLGlueEnvironment: The reward function value range
RewardsCommand - Class in burlap.shell.command.world: A ShellCommand for printing the last joint rewards delivered by a World.
RewardsCommand() - Constructor for class burlap.shell.command.world.RewardsCommand
rewardSequence - Variable in class burlap.behavior.singleagent.Episode: The sequence of rewards received.
RewardValueProjection - Class in burlap.behavior.singleagent.learnfromdemo: This class is a QProvider/ValueFunction wrapper to provide the immediate reward signals for a source RewardFunction.
RewardValueProjection(RewardFunction) - Constructor for class burlap.behavior.singleagent.learnfromdemo.RewardValueProjection: Initializes for the given RewardFunction assuming that it only depends on the destination state.
RewardValueProjection(RewardFunction, RewardValueProjection.RewardProjectionType) - Constructor for class burlap.behavior.singleagent.learnfromdemo.RewardValueProjection: Initializes.
RewardValueProjection(RewardFunction, RewardValueProjection.RewardProjectionType, SADomain) - Constructor for class burlap.behavior.singleagent.learnfromdemo.RewardValueProjection: Initializes.
RewardValueProjection.CustomRewardNoTermModel - Class in burlap.behavior.singleagent.learnfromdemo
RewardValueProjection.RewardProjectionType - Enum in burlap.behavior.singleagent.learnfromdemo
rf - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableDP: The differentiable RF
rf - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling
rf - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.VanillaDiffVinit: The differentiable reward function that defines the parameter space over which this value function initialization must differentiate.
rf - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.MLIRLRequest: The differentiable reward function model that will be estimated by MLRIL.
rf - Variable in class burlap.behavior.singleagent.learnfromdemo.RewardValueProjection
rf - Variable in class burlap.domain.singleagent.blockdude.BlockDude
rf - Variable in class burlap.domain.singleagent.blocksworld.BlocksWorld
rf - Variable in class burlap.domain.singleagent.cartpole.CartPoleDomain
rf - Variable in class burlap.domain.singleagent.cartpole.InvertedPendulum
rf - Variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain
rf - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain
rf - Variable in class burlap.domain.singleagent.gridworld.GridWorldDomain
rf - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderDomain
rf - Variable in class burlap.domain.singleagent.mountaincar.MountainCar
rf - Variable in class burlap.mdp.singleagent.model.FactoredModel
rfDim - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling: The dimensionality of the differentiable reward function
rfDim - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit: The dimensionality of the reward function parameters
rfFeaturesAreForNextState - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit: Whether features are based on the next state or previous state.
rfFvGen - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit: The state feature vector generator.
right - Variable in class burlap.domain.singleagent.lunarlander.state.LLBlock
RLGLueAction(int) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueDomain.RLGlueActionType.RLGLueAction
RLGlueActionType(Domain, int) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueDomain.RLGlueActionType: Initiaizes.
RLGlueAgent - Class in burlap.behavior.singleagent.interfaces.rlglue: An RLGlue Agent that is implemented as a BURLAP Environment, so that any BURLAP RL agent can control the RLGlue agent.
RLGlueAgent() - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent
RLGlueAgent.MutableInt - Class in burlap.behavior.singleagent.interfaces.rlglue: A mutable int wrapper
RLGlueAgent.StateReference - Class in burlap.behavior.singleagent.interfaces.rlglue: A wrapper that maintains a reference to a State or null.
RLGlueDomain - Class in burlap.behavior.singleagent.interfaces.rlglue: A class for generating a BURLAP Domain for an RLGlue TaskSpec.
RLGlueDomain(TaskSpec) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueDomain
RLGlueDomain.RLGlueActionType - Class in burlap.behavior.singleagent.interfaces.rlglue: A BURLAP ActionType that corresponds to an RLGlue action that is defined by a single int value.
RLGlueDomain.RLGlueActionType.RLGLueAction - Class in burlap.behavior.singleagent.interfaces.rlglue
RLGlueEnvironment - Class in burlap.domain.singleagent.rlglue: This class can be used to take a BURLAP domain and task with discrete actions and turn it into an RLGlue environment with which other RLGlue agents can interact.
RLGlueEnvironment(SADomain, StateGenerator, DenseStateFeatures, DoubleRange[], DoubleRange, boolean, double) - Constructor for class burlap.domain.singleagent.rlglue.RLGlueEnvironment: Constructs with all the BURLAP information necessary for generating an RLGlue Environment.
rlGlueExperimentFinished - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent
rlGlueExperimentFinished() - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent: Returns true if the RLGlue experiment is finished; false otherwise.
RLGlueState - Class in burlap.behavior.singleagent.interfaces.rlglue: A State for RLGLue Observation objects.
RLGlueState() - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueState
RLGlueState(Observation) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueState
RLGlueState.RLGlueVarKey - Class in burlap.behavior.singleagent.interfaces.rlglue
RLGlueVarKey(char, int) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueState.RLGlueVarKey
RLGlueVarKey(String) - Constructor for class burlap.behavior.singleagent.interfaces.rlglue.RLGlueState.RLGlueVarKey
RMaxModel - Class in burlap.behavior.singleagent.learning.modellearning.rmax
RMaxModel(KWIKModel, PotentialFunction, double, List<ActionType>) - Constructor for class burlap.behavior.singleagent.learning.modellearning.rmax.RMaxModel
RMaxPotential(double, double) - Constructor for class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax.RMaxPotential: Initializes for a given maximum reward and discount factor.
RMaxPotential(double) - Constructor for class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax.RMaxPotential: Initializes using the given maximum value function value
rollout(Policy, State, SampleModel) - Static method in class burlap.behavior.policy.PolicyUtils: This method will return the an episode that results from following the given policy from state s.
rollout(Policy, State, SampleModel, int) - Static method in class burlap.behavior.policy.PolicyUtils: This method will return the an episode that results from following the given policy from state s.
rollout(Policy, Environment) - Static method in class burlap.behavior.policy.PolicyUtils: Follows the policy in the given Environment.
rollout(Policy, Environment, int) - Static method in class burlap.behavior.policy.PolicyUtils: Follows the policy in the given Environment.
rolloutJointPolicy(JointPolicy, int) - Method in class burlap.mdp.stochasticgames.world.World: Rollsout a joint policy until a terminate state is reached for a maximum number of stages.
rolloutJointPolicyFromState(JointPolicy, State, int) - Method in class burlap.mdp.stochasticgames.world.World: Rollsout a joint policy from a given state until a terminate state is reached for a maximum number of stages.
rolloutOneStageOfJointPolicy(JointPolicy) - Method in class burlap.mdp.stochasticgames.world.World: Runs a single stage following a joint policy for the current world state
rollOutPolicy - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: The policy to use for episode rollouts
rolloutsDecomposeOptions - Static variable in class burlap.behavior.policy.PolicyUtils: Indicates whether rollout methods will decompose Option selections into the primitive Action objects they execute and annotate them with the name of the calling Option in the returned Episode.
root - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
root - Variable in class burlap.datastructures.StochasticTree: Root node of the stochastic tree
rootLevelQValues - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling: The root state node Q-values that have been estimated by previous planning calls.
rootLevelQValues - Variable in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: The root state node Q-values that have been estimated by previous planning calls.
roundNegativesToZero(double[]) - Static method in class burlap.behavior.stochasticgames.solvers.CorrelatedEquilibriumSolver: Creates a new 1D double array with all negative values rounded to 0.
rowCol(int, int) - Static method in class burlap.behavior.stochasticgames.solvers.CorrelatedEquilibriumSolver: Returns the 2D row column index in a matrix of a given number of columns for a given 1D array index.
rowPayoffs - Variable in class burlap.behavior.stochasticgames.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingSGAgent.BimatrixTuple: The row player's payoffs.
RTDP - Class in burlap.behavior.singleagent.planning.stochastic.rtdp: Implementation of Real-time dynamic programming [1].
RTDP(SADomain, double, HashableStateFactory, double, int, double, int) - Constructor for class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: Initializes.
RTDP(SADomain, double, HashableStateFactory, ValueFunction, int, double, int) - Constructor for class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: Initializes.
runEpisodeBoundTrial(LearningAgentFactory) - Method in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter: Runs a trial for an agent generated by the given factory when interpreting trial length as a number of episodes.
runEpisodewiseTrial(World) - Method in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter: Runs a trial where trial length is interpreted as the number of episodes in a trial.
runGame() - Method in class burlap.mdp.stochasticgames.world.World: Runs a game until a terminal state is hit.
runGame(int) - Method in class burlap.mdp.stochasticgames.world.World: Runs a game until a terminal state is hit for maxStages have occurred
runGame(int, State) - Method in class burlap.mdp.stochasticgames.world.World: Runs a game starting in the input state until a terminal state is hit.
runIteration() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Runs a single iteration of value iteration.
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic
runLearningEpisode(Environment) - Method in interface burlap.behavior.singleagent.learning.LearningAgent
runLearningEpisode(Environment, int) - Method in interface burlap.behavior.singleagent.learning.LearningAgent
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.tdmethods.SarsaLam
runLearningEpisode(Environment) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
runLearningEpisode(Environment, int) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
runLPAndGetJointActionProbs(LinearProgram, int, int) - Static method in class burlap.behavior.stochasticgames.solvers.CorrelatedEquilibriumSolver: Helper method for running the linear program optimization (after its constraints have already been set) and returning the result in the form of the 2D double matrix joint strategy.
runPlannerForAllInitStates(Planner, StateConditionTestIterable) - Static method in class burlap.behavior.singleagent.planning.deterministic.MultiStatePrePlanner: Runs a planning algorithm from multiple initial states to ensure that an adequate plan/policy exist for of the states.
runPlannerForAllInitStates(Planner, Collection<State>) - Static method in class burlap.behavior.singleagent.planning.deterministic.MultiStatePrePlanner: Runs a planning algorithm from multiple initial states to ensure that an adequate plan/policy exist for of the states.
runPolicyIteration(int, double) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Runs LSPI for either numIterations or until the change in the weight matrix is no greater than maxChange.
runRollout(State) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Runs a planning rollout from the provided state.
runRolloutsInReverse - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Whether each rollout should be run in reverse after completion.
runStage() - Method in class burlap.mdp.stochasticgames.world.World: Runs a single stage of this game.
runStepBoundTrial(LearningAgentFactory) - Method in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter: Runs a trial for an agent generated by the given factor when interpreting trial length as a number of total steps.
runStepwiseTrial(World) - Method in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter: Runs a trial where the trial lenght is interpreted as the number of total steps taken.
runTournament() - Method in class burlap.mdp.stochasticgames.tournament.Tournament: Runs the tournament
runVI() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableVI: Runs VI until the specified termination conditions are met.
runVI() - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.PrioritizedSweeping
runVI() - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.ValueIteration: Runs VI until the specified termination conditions are met.
runVI() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Runs value iteration.
runVI() - Method in class burlap.behavior.stochasticgames.madynamicprogramming.dpplanners.MAValueIteration: Runs Value Iteration over the set of states that have been discovered.

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